- Open Automator
- Create a new document
- Select Quick Action
- Set “Service receives selected” to
files or foldersinany application - Add a
Run Shell Scriptaction- your default shell should already be selected, otherwise use
/bin/zshfor macOS 10.15 (”Catalina”) or later - older versions of macOS use
/bin/bash
- your default shell should already be selected, otherwise use
- if you're using something else, you probably know what to do 😉
Discover gists
Lecture 1: Introduction to Research — [📝Lecture Notebooks] [
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[
With these steps I managed to get Pimox on my Raspberry Pi 4 and 5 in february 2024.
Install "RPi OS Lite 64-bit" with Raspberry Pi Imager. It's listed under "Raspberry Pi OS (Other)"
Note: This is all almost full YouTube ID informations. Original owner goes to AgentOak, modified version by Martin Eesmaa.
See the credits and also special thanks in below.
Before this gist has been forked, AgentOak made original gist on November 13 2019 and it was last updated on May 5 2021.
From now on, this forked gist is maintained by Martin Eesmaa since 17 September 2022. I joined to yt-dlp Discord server on 3rd April 2026 with my Discord username: martineesmaa.
Last updated: 26 May 2026
This comprehensive guide covers the process of moving movie files into individual folders for a neatly organized Plex Media Server library, and it also explains how to use FileBot to rename files and add posters and artwork for an enhanced media management experience.
Firstly to make the browser see and be able to use the HID device (/dev/hidraw*), we need to make a udev rule:
Check the PID and the VID of your devices:
lsusb | grep Keychron
Bus 003 Device 004: ID 3434:d030 Keychron Keychron Link
Bus 003 Device 009: ID 3434:0960 Keychron Keychron V6 Max
These instructions are based on this blogpost by Anton Semjonov and this video by Animortis Productions. Please follow the link if you want more details, they go into much more detail about each step, whereas this document is more focused on being a concise cheat sheet. Let's go.
Boot the Ubuntu installation medium. When asked, choose the "Try Ubuntu" option and open a terminal.
Switch to root, otherwise you'll have to type sudo all the time:
sudo su -
| { | |
| "domains": [], | |
| "crawl": { | |
| "enable": true, | |
| "exclude": "", | |
| "threshold": 5, | |
| "singlelink": true, | |
| "persist": { | |
| "subs": "crawledsubs", | |
| "proxies": "crawledproxies" |
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| 약자 | 한국정보과학회 (2024) | BK21플러스 IF (2018) | KAIST CS (2025) | SNU CSE (2024.4) | POSTECH CSE (2026.1) | 평균 (정규화) | 학회명 | DBLP Key | |
|---|---|---|---|---|---|---|---|---|---|
| AAAI | 최우수 | 4 | O | O | 최우수 | 1.00 | AAAI Conference on Artificial Intelligence (AAAI) | conf/aaai | |
| AAMAS | 우수 | 2 | 0.20 | International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | conf/ifaamas | ||||
| ACCV | 우수 | 1 | 우수 | 0.25 | Asian Conference on Computer Vision (ACCV) | conf/accv | |||
| ACL | 최우수 | 4 | O | O | 최우수 | 1.00 | Annual Meeting of the Association for Computational Linguistics (ACL) | conf/acl | |
| ACL Findings | 우수 | 우수 | 0.20 | Findings of ACL | series/findacl | ||||
| ACNS | 우수 | 0.10 | International Conference on Applied Cryptography and Network Security (ACNS) | conf/acns | |||||
| ACSAC | 우수 | 2 | 우수 | 0.30 | Annual Computer Security Applications Conference (ACSAC) | conf/acsac | |||
| AIED | 우수 | 0.10 | International Conference on Artificial Intelligence in Education (AIED) | conf/aied | |||||
| AISTATS | 우수 | 1 | 우수 | 0.25 | International Conference on Artificial Intelligence and Statistics (AISTATS) | conf/aistats |
